Relational databases can be accessed by modern querying languages such as Structured Query Language (SQL), which supports a broad range of querying mechanisms. But SQL interfaces can be difficult for non-software developers to design search queries in these languages. As such, these lower-quality queries cause lower-quality results.
Some solutions exist for translating natural language (NL) queries to database queries. But these solutions are deficient. For example, some solutions can use trained neural networks to perform the translation. But these solutions suffer from issues. For example, a large training dataset may be needed, and the solutions are domain-specific.
Hence, new solutions are needed that can translate natural language queries into modern querying languages.